Degenerate Motion Analysis for Aided INS With Online Spatial and Temporal Sensor Calibration

被引:63
|
作者
Yang, Yulin [1 ]
Geneva, Patrick [2 ]
Eckenhoff, Kevin [1 ]
Huang, Guoquan [1 ]
机构
[1] Univ Delaware, Dept Mech Engn, Newark, DE 19716 USA
[2] Univ Delaware, Dept Comp & Informat Sci, Newark, DE 19716 USA
基金
美国国家科学基金会;
关键词
Calibration and identification; visual-based navigation; inertial navigation system; observability analysis; KALMAN FILTER;
D O I
10.1109/LRA.2019.2893803
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
In this letter, we perform in-depth observability analysis for both spatial and temporal calibration parameters of an aided inertial navigation system (INS) with global and/or local sensing modalities. In particular, we analytically show that both spatial and temporal calibration parameters are observable if the sensor platform undergoes random motion. More importantly, we identify four degenerate motion primitives that harm the calibration accuracy and thus should be avoided in reality whenever possible. Interestingly, we also prove that these degenerate motions would still hold even in the case where global pose measurements are available. Leveraging a particular multi-state constrained Kalman filter based vision-aided INS with online spatial and temporal calibration, we perform extensively both Monte-Carlo simulations and real-world experiments with the identified degenerate motions to validate our analysis.
引用
收藏
页码:2070 / 2077
页数:8
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